Resumen

CAMPOS-ARANDA, Daniel Francisco. Comparison of RDI based on PET in three climatic locations in San Luis Potosi, Mexico. Tecnol. cienc. agua [online]. 2018, vol.9, n.4, pp.147-183.  Epub 24-Nov-2020. ISSN 2007-2422.  https://doi.org/10.24850/j-tyca-2018-04-07.

Meteorological droughts are a recurring natural phenomenon that causes lack of precipitation. The severity of meteorological droughts is estimated by established algorithms known as drought indices. One such procedure, perhaps the simplest, is the Reconnaissance Drought Index, or RDI, which is based on the ratio between precipitation and potential evapotranspiration (PET) for a determined continuous period of months. In this study, the RDI is applied to three durations of meteorological drought at a weather station selected from each of the three geographic or climate zones in the state of San Luis Potosi, Mexico, which are: Villa de Arriaga (Potosino Plateau), Río Verde (Mean Zone), and Xilitla (Huasteca Region). The monthly rainfall records and average and minimum temperatures of each station cover more than 50 years. PET was estimated by four methods: (1) the Penman-Monteith formula, which is the reference method, (2) the Thornthwaite, (3) the Turc, and (4) the Hargreaves-Samani. The operating procedures for these criteria are detailed in appendices. The analysis of the results indicates that the RDIs estimated with the Hargreaves-Samani method are best for reproducing the results of the Penman-Monteith formula, in the three climatic locations processed. The Turc method also led to results similar to those of the reference. Therefore, it can be said that the RDI is a robust drought index, which practically does not depend on the method of estimating the PET. There is a noticeable difference in the operational procedures of the Penman-Monteith formula and the Hargreaves-Samani method. The latter is a practical solution that is worth mentioning.

Palabras llave : Meteorological droughts; potential evapotranspiration; statistical tests; mean square error; mean bias error; types of meteorological drought (light,moderate,severe and extreme).

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